Claude Fable 5 vs Kimi K2.7 Code
Claude Fable 5 leads Kimi K2.7 Code on coding, 79.3 to 53.4 on the Vibe Coding Index, and Kimi K2.7 Code costs 12.5x less per output token ($4.00 vs $50.00 per million). Updated October 21, 2026; 50 benchmarks have a result for both.
Claude Fable 5 or Kimi K2.7 Code: which to pick
Pick Claude Fable 5 for coding: it scores 79.3 on the Vibe Coding Index against 53.4 for Kimi K2.7 Code.
Pick Kimi K2.7 Code for output tokens 12.5x cheaper ($4.00 vs $50.00 per million) and a lower cost per solved task ($0.35 against $2.16).
- Shared results
- 50
- Claude Fable 5 only
- 77
- Kimi K2.7 Code only
- 1
- Like-for-like categories
- 8 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
Claude Fable 5
Claude Fable 5 scores 79.3 against 53.4.
6 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
Claude Fable 5
Claude Fable 5 leads, 49.6 against 25.8.
Same board, both measured
Agentic work
AA Agentic Index
Claude Fable 5
Claude Fable 5 leads, 50.7 against 21.0.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Claude Fable 5 has a GPQA Diamond result, 93.2%.
Directional only
Knowledge
MMLU Pro
No call
Only Claude Fable 5 has a MMLU Pro result, 91.5%.
Directional only
Web design
Design Arena: websites
Claude Fable 5
Claude Fable 5 leads, 1296 against 1264.
Same board, both measured
Long documents
Listed context window
Claude Fable 5
Claude Fable 5 takes 1M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Kimi K2.7 Code
Claude Fable 5 $0.035, Kimi K2.7 Code $0.0029 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Kimi K2.7 Code
Claude Fable 5 $2.16, Kimi K2.7 Code $0.35.
Published attempt cost and pass rate
At a glance
- Coding index
- Claude Fable 5 79.3 from 6 benchmarks, Kimi K2.7 Code 53.4 from 4 benchmarks.
- Widest category
- Math, 38.5 points apart on average over 3 shared benchmarks.
- Widest single gap
- FrontierMath, tier 4: Claude Fable 5 90.2% against Kimi K2.7 Code 12.2%, 78.0 points apart on a 0 to 100 scale.
- Output price
- Claude Fable 5 $50.00 against Kimi K2.7 Code $4.00 per million output tokens, 12.5x apart.
- Context window
- Claude Fable 5 takes 1M tokens, Kimi K2.7 Code 262K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Claude Fable 5 | Bars | Kimi K2.7 Code | Ties |
|---|---|---|---|---|
| Coding | 16 | 0 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 12 | 0 | ||
| Reasoning | 4 | 1 | ||
| Math | 3 | 0 | ||
| Knowledge | 1 | 0 | ||
| Web design | 8 | 0 | ||
| General | 3 | 0 | ||
| All shared boards | 49 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index160
| Benchmark | Claude Fable 5 | Kimi K2.7 Code | Leader |
|---|---|---|---|
| LiveBench coding | 98.3% | Not measured | Only Claude Fable 5 measured |
| LMArena WebDev | 1624 | 1474 | Claude Fable 5 |
| AA Coding Index | 76.5 | 60.8 | Claude Fable 5 |
| LiveCodeBench (Vals AI) | 89.8% | 82.0% | Claude Fable 5 |
| SWE-bench Verified (Vals AI) | 95.0% | 78.2% | Claude Fable 5 |
| Terminal-Bench 4 (Vals AI) | 41.4% | Not measured | Only Claude Fable 5 measured |
| Vibe Code Bench (Vals AI) | 90.3% | 47.2% | Claude Fable 5 |
| Code migration (Vals AI) | 55.1% | 25.4% | Claude Fable 5 |
| ProgramBench (Vals AI) | 2.0% | 0.0% | Claude Fable 5 |
| Terminal-Bench 2.1 (Vals AI) | 80.5% | 67.0% | Claude Fable 5 |
| SkillsBench (Vals AI) | Not measured | 50.0% | Only Kimi K2.7 Code measured |
| SciCode | 61.0% | 47.8% | Claude Fable 5 |
| Terminal-Bench Hard (Artificial Analysis run) | 62.9% | 44.7% | Claude Fable 5 |
| FrontierCode | 53.5% | 30.1% | Claude Fable 5 |
| FrontierSWE | 47.0% | Not measured | Only Claude Fable 5 measured |
| GSO-Bench | 78.4% | Not measured | Only Claude Fable 5 measured |
| WeirdML | 91.9% | 54.1% | Claude Fable 5 |
| MirrorCode | 63.9% | Not measured | Only Claude Fable 5 measured |
| ALE-Bench | 2041.3 | 886.2 | Claude Fable 5 |
| LMArena Text: coding | 1518 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: software and IT | 1513 | Not measured | Only Claude Fable 5 measured |
| LMArena WebDev: React | 1631 | 1475 | Claude Fable 5 |
| LMArena WebDev: HTML | 1651 | 1451 | Claude Fable 5 |
| LMArena WebDev: from an image | 1623 | 1513 | Claude Fable 5 |
| Neither model has a result on the other 15 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Claude Fable 5 | Kimi K2.7 Code | Leader |
|---|---|---|---|
| AA Intelligence Index | 49.6 | 25.8 | Claude Fable 5 |
| Epoch Capabilities Index | 163.4 | 150.1 | Claude Fable 5 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index120
| Benchmark | Claude Fable 5 | Kimi K2.7 Code | Leader |
|---|---|---|---|
| AA Agentic Index | 50.7 | 21.0 | Claude Fable 5 |
| Design Arena: agents building web apps | 1261 | 1176 | Claude Fable 5 |
| Design Arena: agents building full-stack apps | 1280 | 1175 | Claude Fable 5 |
| Design Arena: agents building mobile apps | 1264 | 1143 | Claude Fable 5 |
| Design Arena: agents building Android apps | 1283 | 1137 | Claude Fable 5 |
| Design Arena: agents building Godot games | 1292 | 1147 | Claude Fable 5 |
| Design Arena: agents building games | 1285 | 1131 | Claude Fable 5 |
| Design Arena: HTML slides | 1277 | 1201 | Claude Fable 5 |
| Design Arena: PowerPoint slides | 1295 | 1154 | Claude Fable 5 |
| LiveBench research | 86.9% | Not measured | Only Claude Fable 5 measured |
| LiveBench browser | 92.0% | Not measured | Only Claude Fable 5 measured |
| LiveBench long agentic | 53.2% | Not measured | Only Claude Fable 5 measured |
| Finance Agent (Vals AI) | 56.3% | Not measured | Only Claude Fable 5 measured |
| Tax Agent Bench (Vals AI) | 38.3% | Not measured | Only Claude Fable 5 measured |
| Legal Research Bench (Vals AI) | 49.5% | Not measured | Only Claude Fable 5 measured |
| Excel Modeling Benchmark (Vals AI) | 73.7% | Not measured | Only Claude Fable 5 measured |
| Terminal-Bench-Science (Vals AI) | 15.7% | Not measured | Only Claude Fable 5 measured |
| τ²-Bench Telecom | 98.5% | 90.1% | Claude Fable 5 |
| APEX-Agents | 63.6% | 37.6% | Claude Fable 5 |
| Remote Labor Index | 16.1% | Not measured | Only Claude Fable 5 measured |
| PostTrainBench | 41.8% | Not measured | Only Claude Fable 5 measured |
| Vending-Bench 2 | $5,680 | $5,083 | Claude Fable 5 |
| LMArena Search | 1229 | Not measured | Only Claude Fable 5 measured |
| Neither model has a result on the other 18 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index41
| Benchmark | Claude Fable 5 | Kimi K2.7 Code | Leader |
|---|---|---|---|
| GPQA Diamond | 93.2% | Not measured | Only Claude Fable 5 measured |
| LiveBench reasoning | 89.7% | Not measured | Only Claude Fable 5 measured |
| MMMU Pro (Vals AI) | 89.3% | Not measured | Only Claude Fable 5 measured |
| GPQA Diamond (Artificial Analysis run) | 92.6% | 89.6% | Claude Fable 5 |
| Humanity's Last Exam (Artificial Analysis run) | 55.5% | 35.0% | Claude Fable 5 |
| GPQA Diamond (Epoch AI run) | 85.9% | 87.9% | Kimi K2.7 Code |
| ARC-AGI | 98.5% | Not measured | Only Claude Fable 5 measured |
| ARC-AGI-2 | 89.2% | Not measured | Only Claude Fable 5 measured |
| SimpleBench | 81.9% | 57.9% | Claude Fable 5 |
| Chess puzzles | 47.0% | 14.0% | Claude Fable 5 |
| Mystery game puzzles | 52.0% | Not measured | Only Claude Fable 5 measured |
| EBR-bench | 39.5% | Not measured | Only Claude Fable 5 measured |
| LMArena Text: hard prompts | 1507 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: expert | 1534 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: hard prompts in English | 1509 | Not measured | Only Claude Fable 5 measured |
| LMArena Vision: diagrams | 1357 | Not measured | Only Claude Fable 5 measured |
| LMArena Vision: homework | 1361 | Not measured | Only Claude Fable 5 measured |
| Kagi LLM Benchmark | 91.4% | Not measured | Only Claude Fable 5 measured |
| Neither model has a result on the other 4 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Claude Fable 5 | Kimi K2.7 Code | Leader |
|---|---|---|---|
| OTIS Mock AIME | 100.0% | 95.6% | Claude Fable 5 |
| FrontierMath, tiers 1 to 3 | 87.0% | 54.0% | Claude Fable 5 |
| FrontierMath, tier 4 | 90.2% | 12.2% | Claude Fable 5 |
| ProofBench | 95.0% | Not measured | Only Claude Fable 5 measured |
| LMArena Text: math | 1516 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: mathematical work | 1515 | Not measured | Only Claude Fable 5 measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Claude Fable 5 | Kimi K2.7 Code | Leader |
|---|---|---|---|
| MMLU Pro | 91.5% | Not measured | Only Claude Fable 5 measured |
| LegalBench (Vals AI) | 88.6% | Not measured | Only Claude Fable 5 measured |
| CorpFin (Vals AI) | 71.8% | Not measured | Only Claude Fable 5 measured |
| TaxEval (Vals AI) | 76.9% | Not measured | Only Claude Fable 5 measured |
| MortgageTax (Vals AI) | 68.9% | Not measured | Only Claude Fable 5 measured |
| MedCode (Vals AI) | 56.1% | Not measured | Only Claude Fable 5 measured |
| SimpleQA Verified | 70.7% | 36.5% | Claude Fable 5 |
| LMArena Text: science | 1506 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: medicine and healthcare | 1480 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: legal and government | 1498 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: business and finance | 1480 | Not measured | Only Claude Fable 5 measured |
| Neither model has a result on the other 7 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | Claude Fable 5 | Kimi K2.7 Code | Leader |
|---|---|---|---|
| Design Arena: websites | 1296 | 1264 | Claude Fable 5 |
| Design Arena: UI components | 1319 | 1259 | Claude Fable 5 |
| Design Arena: game dev | 1335 | 1220 | Claude Fable 5 |
| Design Arena: data viz | 1304 | 1227 | Claude Fable 5 |
| Design Arena: 3D | 1319 | 1241 | Claude Fable 5 |
| Design Arena: all code categories | 1310 | 1253 | Claude Fable 5 |
| Design Arena: SVG | 1302 | 1176 | Claude Fable 5 |
| Design Arena: ASCII art | 1329 | 1196 | Claude Fable 5 |
| LiveBench design | 84.7% | Not measured | Only Claude Fable 5 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Claude Fable 5 | Kimi K2.7 Code | Leader |
|---|---|---|---|
| LiveBench data analysis | 80.5% | Not measured | Only Claude Fable 5 measured |
| Public Benefits Bench (Vals AI) | 70.4% | Not measured | Only Claude Fable 5 measured |
| SAGE (Vals AI) | 51.9% | Not measured | Only Claude Fable 5 measured |
| MedScribe (Vals AI) | 88.5% | Not measured | Only Claude Fable 5 measured |
| Vals Multimodal Index | 74.2% | Not measured | Only Claude Fable 5 measured |
| IFBench | 63.5% | 63.1% | Claude Fable 5 |
| Long context reasoning (AA-LCR) | 82.3% | 79.3% | Claude Fable 5 |
| DTBench | 98.4% | Not measured | Only Claude Fable 5 measured |
| LMCA | 61.2% | Not measured | Only Claude Fable 5 measured |
| Surface Evolver Bench | 95.0% | 48.8% | Claude Fable 5 |
| Furniture assembly | 35.8% | Not measured | Only Claude Fable 5 measured |
| LMArena Text | 1491 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: instruction following | 1502 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: creative writing | 1494 | Not measured | Only Claude Fable 5 measured |
| LMArena Vision | 1325 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: English | 1498 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: non-English | 1482 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: Chinese | 1543 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: German | 1486 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: Japanese | 1504 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: Korean | 1487 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: French | 1505 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: Spanish | 1498 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: Russian | 1503 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: Polish | 1494 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: multi-turn | 1504 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: longer queries | 1510 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: writing and language | 1501 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: entertainment and media | 1482 | Not measured | Only Claude Fable 5 measured |
| LMArena Vision: English | 1323 | Not measured | Only Claude Fable 5 measured |
| LMArena Vision: Chinese | 1373 | Not measured | Only Claude Fable 5 measured |
| LMArena Vision: reading text | 1337 | Not measured | Only Claude Fable 5 measured |
| LMArena Vision: humor | 1341 | Not measured | Only Claude Fable 5 measured |
| LMArena Vision: creative writing | 1338 | Not measured | Only Claude Fable 5 measured |
| LMArena Document | 1496 | Not measured | Only Claude Fable 5 measured |
| Neither model has a result on the other 11 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Claude Fable 5 | Kimi K2.7 Code | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Kimi K2.7 Code costs less
Repository review
50K input + 3K output tokens
Kimi K2.7 Code costs less
Agent loop
200K input + 10K output tokens
Kimi K2.7 Code costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Anthropic Claude Fable 5 | MoonshotAI Kimi K2.7 Code |
|---|---|---|
| Maker | Anthropic | Moonshot AI |
| Weights | No public weights listed | Open weights |
| Released | June 9, 2026 | June 12, 2026 |
| Context window | 1M | 262K |
| Input $/Mtok | $10.00 | $0.95 |
| Output $/Mtok | $50.00 | $4.00 |
| Coding index | 79.3 | 53.4 |
| Independent measurements behind it | 6 | 4 |
| Cost per solved task | $2.16 | $0.35 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Claude Fable 5 better than Kimi K2.7 Code for coding?
Pick Claude Fable 5 for coding: it scores 79.3 on the Vibe Coding Index against 53.4 for Kimi K2.7 Code. Pick Kimi K2.7 Code for output tokens 12.5x cheaper ($4.00 vs $50.00 per million) and a lower cost per solved task ($0.35 against $2.16).
Which is cheaper, Claude Fable 5 or Kimi K2.7 Code?
Claude Fable 5 costs $10.00 per million input tokens and $50.00 per million output tokens; Kimi K2.7 Code costs $0.95 and $4.00. Per solved SWE-bench Verified task, Claude Fable 5 costs $2.16 and Kimi K2.7 Code $0.35.
Which has the bigger context window, Claude Fable 5 or Kimi K2.7 Code?
Claude Fable 5, with 1M tokens against 262K.
How many benchmarks is the Claude Fable 5 vs Kimi K2.7 Code comparison based on?
50 benchmarks have a result for both models as of October 21, 2026. Claude Fable 5's coding index rests on 6 independent benchmarks and Kimi K2.7 Code's on 4. Where only one model has a result, the page says so instead of naming a winner.